Equipment knowledge base construction method based on digital and intelligent application

Abstract

The invention discloses an equipment knowledge base construction method based on digital and intelligent application. The method comprises the following steps: 1, ; five key fields of an asset structure, a fault mode, a fault reason, a maintenance strategy and a health index description fault or defect are distributed in an asset structure library, a fault mode library, a maintenance strategy library and a health index library, and an equipment knowledge base is constructed; by analyzing the internal logic among different fields, the incidence relation among the fields is established, four standard libraries are established, and an equipment knowledge base is constructed. According to the method, the solving efficiency can be improved, the labor cost is reduced, Meanwhile, an enterprise isassisted to formulate a maintenance strategy better conforming to the enterprise and gradually form a knowledge base.

Description

technical field [0001] The invention relates to the field of equipment management, in particular to a method for constructing an equipment knowledge base based on digital and intelligent applications. Background technique [0002] In traditional industrial industries such as electric power, petroleum, and chemical industry, industrial equipment is the core asset of the enterprise, and the management of equipment is one of the key factors to maintain the safety and production of the enterprise. Enterprises have accumulated a lot of experience and knowledge about equipment in daily production activities and troubleshooting, but these experiences and knowledge have not been recorded in effective data, which can neither solidify and inherit the experience of excellent experts, nor help Management improves decision-making efficiency and makes scientific decisions. [0003] With the continuous development of modern information technology and the continuous improvement of enterpri...

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Problems solved by technology

[0004] However, at present, the records of equipment failures and defects in industrial enterprises are usually discrete. On the one hand, enterprises generate a large amount of data, on the other hand, the data often form isolated islands, and the data value is difficult to be exploited

A small number of advanced enterprises use fault databases to record equipment faults and defect information. This type of database usually has structured defect fields for engineers to fill in and use. It can simply classify defects and solve some digital problems, but it does not establish the relationship between data relationship, cannot form a knowledge map, and cannot accumulate and update experience and knowledge

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